The present invention relates to wireless communication systems. More specifically, the invention relates to methods for enhancement of wireless communication performance by exploiting the spatial domain, and practical systems for implementing such methods.
Due to the increasing demand for wireless communication, it has become necessary to develop techniques for more efficiently using the allocated frequency bands, i.e., increasing the capacity to communicate information within a limited available bandwidth. In conventional low capacity wireless communication systems, information is transmitted from a base station to subscribers by broadcasting omnidirectional signals on one of several predetermined frequency channels. Similarly, the subscribers transmit information back to the base station by broadcasting similar signals on one of the frequency channels. In this system, multiple users independently access the system through the division of the frequency band into distinct subband frequency channels. This technique is known as frequency division multiple access (FDMA).
A standard technique used by commercial wireless phone systems to increase capacity is to divide the service region into spatial cells. Instead of using just one base station to serve all users in the region, a collection of base stations are used to independently service separate spatial cells. In such a cellular system, multiple users can reuse the same frequency channel without interfering with each other, provided they access the system from different spatial cells. The cellular concept, therefore, is a simple type of spatial division multiple access (SDMA).
In the case of digital communication, additional techniques can be used to increase capacity. A few well known examples are time division multiple access (TDMA) and code division multiple access (CDMA). TDMA allows several users to share a single frequency channel by assigning their data to distinct time slots. CDMA is normally a spread-spectrum technique that does not limit individual signals to narrow frequency channels but spreads them throughout the frequency spectrum of the entire band. Signals sharing the band are distinguished by assigning them different orthogonal digital code sequences. CDMA has been considered the most promising method among the various air-interfaces in the industry, as shown by theoretical analysis and recent increase in use.
Despite the promise of CDMA, practical issues such as power control speed and inter-base station interference considerably limited system effectiveness in its initial phase of implementation. CDMA based system capacity depends very much on the ability to provide for very accurate power control; but in a mobile environment, the signal may fluctuate too fast for the system to manage effective control. In addition, mobile wireless environments are often characterized by unstable signal propagation, severe signal attenuation between the communicating entities and co-channel interference by other radio sources. Moreover, many urban environments contain a significant number of reflectors (such as buildings), causing a signal to follow multiple paths from the transmitter to the receiver. Because the separate parts of such a multipath signal can arrive with different phases that destructively interfere, multipath can result in unpredictable signal fading. In addition, in order to provide service to shadowed areas, radiated power is increased, thereby increasing interference between base stations and significantly degrading system performance.
Recently, considerable attention has focused on ways to increase wireless system performance by further exploiting the spatial domain. It is well recognized that SDMA techniques could, in principle, significantly improve the CDMA based network performance. In practice, however, such significant improvements have yet to be realized. Currently proposed approaches are either simple but not very effective or effective but too complex for practical implementation.
One well-known SDMA technique is to provide the base station with a set of independently controlled directional antennas, thereby dividing the cell into separate fixed sectors, each controlled by a separate antenna. As a result, the frequency reuse in the system can be increased and/or cochannel interference can be reduced. A similar but more complex technique can be implemented with a coherently controlled antenna array instead of independently controlled directional antennas. Using a signal processor to control the relative phases of the signals applied to the antenna array elements, predetermined beams can be formed in the directions of the separate sectors. Similar signal processing can be used to selectively receive signals only from within the distinct sectors. These simple sectoring techniques, however, only provide a relatively small increase in capacity.
U.S. Pat. No. 5,563,610 discloses a method for mitigating signal fading due to multipath in a CDMA system. By introducing intentional delays into received signals, non-correlated fading signal components can be better differentiated by the RAKE receiver. Although this diversity method can reduce the effects of fading, it does not take advantage of the spatial domain and does not directly increase system capacity. Moreover, this approach, which combines angular and time diversity using a fixed beam configuration, is not effective since either the beam outputs are significantly different in level or they are similar in level but highly correlated. If two signal parts are arriving from a similar direction, they are passing through one beam and thus are not spatially distinguishable. If the signal parts are arriving between beams, on the other hand, the levels are similar but then they are highly correlated.
More sophisticated SDMA techniques have been proposed that theoretically could dramatically increase system capacity. For example, U.S. Pat. Nos. 5,471,647 and 5,634,199, both to Gerlach et al., and U.S. Pat. No. 5,592,490 to Barratt et al. disclose wireless communication systems that increase performance by exploiting the spatial domain. In the downlink, the base station determines the spatial channel of each subscriber and uses this channel information to adaptively control its antenna array to form customized narrow beams. These beams transmit an information signal over multiple paths so that the signal arrives to the subscriber with maximum strength. The beams can also be selected to direct nulls to other subscribers so that cochannel interference is reduced. In the uplink, the base station uses the channel information to spatially filter the received signals so that the uplink signal is received with maximum sensitivity and distinguished from the signals transmitted by other subscribers. Through selective power delivery by intelligent directional beams, the interference between base stations and the carrier-to-interference ratio at the base station receivers can be reduced.
The biggest issue in adaptive beamforming is how to quickly estimate the wireless air channel to allow for effective beam allocation. In the uplink, there are known signal processing techniques for estimating the spatial channel from the signals received at the base station antenna array. These techniques conventionally involve an inversion or singular value decomposition of a signal covariance matrix. The computational complexity of this calculation, however, is so high that it is presently not practical to implement. These highly complex approaches capitalize on the theory of array signal processing. These approaches estimate the uplink channel (e.g. the angles and times of arrival of the multipath signal parts) to create a space-time matched filter to allow for maximum signal delivery. The method involves computation of a signal covariance matrix and derivation of its eigenvectors to determine the array coefficients. The basic equation of array signal processing is:
X=AS+N,
where X is a matrix of antenna array signal snapshots (each column incorporates snapshots of all antenna elements), S is the transmitted signal matrix (each column incorporates snapshots of the information signal, A is the antenna array and channel response matrix, and N is the noise matrix. The main challenge of array signal processing is to estimate S based on the statistics of A and S, that is, to reliably and correctly estimate all the incoming signals despite the presence of interference and thermal noise, N. This problem has been a subject for extensive research for several years. Two well known estimating algorithms involve Maximum Likelihood Sequence Estimation (MLSE) and Minimum Mean Square Error (MMSE). Using these techniques, if S represents signals with-known properties such as constant modules (CM), or finite alphabet (FA), the process can be executed using the known signal""s temporal structure statistics. If the array manifold is known, then convergence can be made faster. This process, however, is very computational intensive. In a typical base station that must simultaneously support more than 100 mobile units, the computational power is presently beyond practical realization.
Most adaptive beam forming methods described in the art (e.g. U.S. Pat. No. 5,434,578) deal extensively with uplink estimation, while requiring extensive computational resources. Few, however, deal with downlink estimation, which is a more difficult problem. Because the spatial channel is frequency dependent and the uplink and downlink frequencies are often different, the uplink beamforming techniques do not provide the base station with sufficient information to derive the downlink spatial channel information and improve system capacity. One technique for obtaining downlink channel information is to use feedback from the subscriber. The required feedback rates, however, make this approach impractical to implement.
There is a need, therefore, for significantly increasing wireless system capacity using beamforming methods that overcome the limitations in the known approaches.
The present invention provides a method for wireless communication that exploits the spatial domain in both uplink and downlink without requiring computationally complex processing. Surprisingly, the method provides for significant capacity enhancement in both uplink and downlink while maintaining implementation simplicity. This goal is achieved by eliminating the necessity for covariance matrix processing, using low bit count arithmetic and by capitalizing on signal multipath structures.
A method for wireless communication according to the present invention comprises transmitting from a mobile unit a code modulated signal, such as a CDMA signal, which is obtained by modulating original symbols by a predetermined pseudo-noise sequence. The original symbols represent an original information signal. A base station antenna array then receives in parallel N complex valued signal sequences from N corresponding antenna elements. Each of the N signal sequences are then correlated with the pseudo-noise sequence to despread and select N received signals comprising N received symbols corresponding to a common one of the original symbols. The N received symbols are then transformed in parallel to obtain N complex-valued transformer outputs which are then correlated collectively with a set of complex array calibration vectors to obtain spatial information about the signal. Each array calibration vector represents a response of the antenna array to a calibration signal originating in a predetermined direction relative to the base station. The above steps are repeated to obtain spatial information about multiple signal components corresponding to the same mobile. This spatial information is then used to spatially filter subsequent complex valued signal sequences. The filtered signal is then demodulated to obtain a symbol from the original information signal.
The original symbols are selected from a finite symbol alphabet. In a preferred embodiment, the finite alphabet contains not more than 64 symbols and the calibration vectors comprise complex valued components having 1-bit plus sign real part and 1-bit plus sign imaginary part. This simple representation permits the correlation to be computed using only addition, i.e., without the need for computationally complex multiplications. In one embodiment, the correlating step yields spatial information about multiple signal components from the mobile having small time separated signal parts (i.e., having a time spread less than one chip). Another embodiment of the invention includes the step of tracking time and angle information of the multiple signal components.
The invention further provides for spatially filtering a downlink information signal in accordance with the spatial information about the multiple signal components that were determined from the uplink. The spatial filtering comprises assigning the mobile unit to a beam based on spatial information about the mobile. This spatial information comprises directional and distance information about the mobile. The downlink beams are a dynamically adaptive set of overlapping broad and narrow beams such that closer mobiles are assigned to broader beams and more distant mobiles are assigned to narrower beams. The set of beams are modified depending on the statistics of the spatial information of all mobiles served by the base station in order to optimize system performance. In the preferred embodiment, the transmitting of the downlink beams is performed in accordance with beamforming information comprising complex valued elements having 3-bit-plus-sign real part and 3-bit-plus-sign imaginary part.
The invention also provides a CDMA base station implementing the above method. The station comprises an antenna array having N antenna elements, and a set of N receivers coupled to the N antenna elements to produce N incoming signals. The base station also comprises a set of N despreaders coupled to the N receivers for producing from the N incoming signals N despread signals corresponding to a single mobile unit. A set of N symbol transformers is coupled to the N despreaders and produces a complex-valued output from the despread signals. A spatial correlator coupled to the N symbol transformers correlates the complex-valued output with stored array calibration data to produce beamforming information for multiple signal parts associated with the mobile unit. In the preferred embodiment, the array calibration data is composed of complex valued array response elements represented as bit-plus-sign imaginary parts and bit-plus-sign real parts. A receiving beamformer coupled to the spatial correlator and to the N receivers then spatially filters the N incoming signals in accordance with the beamforming information. A RAKE receiver (or other equivalent receiver) coupled to the receiving beamformer produces from the spatially filtered signals an information signal. In one embodiment, the base station also includes a tracker coupled to the spatial correlator and to the receiving beamformer. The tracker tracks multiple signal parts and optimizes the performance of the receiving beamformer.
In the preferred embodiment, the base station also includes a transmitting beamformer coupled to the spatial correlator. The transmitting beamformer generates spatial beams in accordance with the beamforming information to increase system capacity. The spatial beams are a dynamically calculated set of downlink beams comprising narrow beams and overlapping broad beams such that the narrow beams are phase matched to the overlapping wide beams. The spatial beams are selected such that more distant mobiles are assigned to narrower beams and closer mobiles are assigned to broader beams.